Identification of power system primary arcs based on pulse density

ABSTRACT

A diagnostic instrument distinguishes primary arcs from other electrical discharges in an electric power system based on pulse time density of radio frequency noise caused by the discharges. The instrument counts a maximum number of noise pulses in any small time window over a period, and identifies the discharges as primary arcs if the pulse time density is in a range characteristics of primary arcs.

CROSS REFERENCE TO RELATED APPLICATION

This application claims priority from U.S. Provisional Application No.61/094,716, filed Sep. 5, 2008, which application is incorporated hereinby reference.

BACKGROUND

Electrical discharges or arcs in the form of sparks and corona arepresent on virtually all electrical power distribution systems. Sparkscan sometimes be seen as small bright flashes, while corona cansometimes be seen as a bluish glow around high voltage wires. They alsocreate audible crackling or sizzling noise. Moreover, the dischargesgenerate radio frequency (RF) noise that can be heard as static orbuzzing on radio receivers, such as on HAM radio receivers.

Some sparks occur right on the primary and/or secondary conductors.These electrical discharges are herein called “primary arcs.” Othersparks occur on hardware located on the same structure as the conductor,but are not connected to the conductor. These other discharges areherein termed “induced voltage sparks.” These arcs are also known in theelectrical power industry by various other terminologies. Primary arcshave high probability of leading to catastrophic equipment failure,whereas induced voltage sparks are primarily a concern for being asource of radio frequency (RF) interference while not necessarily beingindicative of imminent equipment failure.

There are so many sparks on power lines and power poles that electricpower utilities simply cannot fix all of them. In fact, most sparks areinnocuous from a system reliability perspective. However, “primary arcs”usually carry current and are a warning sign of potential equipmentfailure. Being able to reliably and simply identify these dischargeswould permit a utility to better focus their repair efforts and moreefficiently utilize available maintenance resources. Being able todistinguish from the RF or other noise detected by an RF receiver orother sensor whether the source is a primary arc or induced voltagesparks therefore is desirable.

SUMMARY

The following Detailed Description concerns techniques and instrumentsto distinguish primary arcs from other electrical discharges in anelectrical power system. The techniques and instruments sense noisepulses in a received radio frequency or other sensor signal that arecaused by power system electrical discharges. A measurement relating totime density of the noise pulses within a period of less than one orboth halves of the power system cycle is calculated (e.g., occurrencesper unit time in the time domain), and analyzed to determined whetherthe measurement is characteristic of primary arcs. In one illustratedimplementation for example, a diagnostic instrument measures a maximumcount of the noise pulses in any 100 μsec window over a period of 250milliseconds, and identifies the discharges are primary arcs if thispulse time density measurement exceeds about 5 pulses per window.

This Summary is provided to introduce a selection of concepts in asimplified form that is further described below in the DetailedDescription. This summary is not intended to identify key features oressential features of the claimed subject matter, nor is it intended tobe used as an aid in determining the scope of the claimed subjectmatter. Additional features and advantages of the invention will be madeapparent from the following detailed description of embodiments thatproceeds with reference to the accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a circuit block diagram of a diagnostic instrument fordistinguishing power system primary arcs from among other power lineradio frequency interference sources.

FIG. 2 is a flow diagram of an operating process performed by theapparatus in FIG. 1 to distinguish power system primary arcs from amongother power line radio frequency interference sources.

FIG. 3 is a flow diagram of an alternative operating process performedby the apparatus in FIG. 1 to distinguish power system primary arcs fromamong other power line radio frequency interference sources.

FIG. 4 is a flow diagram of an extension to the operating process ofFIG. 2 or FIG. 3 to further distinguish sparking primary arcs fromcorona.

FIG. 5 is a circuit block diagram of an alternative implementation of adiagnostic instrument for distinguishing system primary arcs.

DETAILED DESCRIPTION

The following detailed description concerns techniques and tools fordistinguishing primary arcs from induced sparks on electric power linesand equipment. The described techniques characterize the source of powersystem sparks based on time density of electrical discharges within ahalf cycle of the alternating current electric power transmission. Thetechnique is described with reference to its implementation in aparticular power system diagnostic instrument. One example of thetechnique is housed in a diagnostic instrument that can be mounted in avehicle, so as to allow a utility employee to patrol a geographic areaof the electric system using the instrument to monitor for sparking orstatic activity and diagnose primary arcs. Alternatively, the diagnosticinstrument can be a handheld, luggable or otherwise portable unit thatthe utility employee can carry in the field to locate and diagnoseprimary arc sparking. The example implementation of the technique isdescribed in the context of a dedicated or specific purpose instrument,but alternatively can be implemented as a multi-purpose instrument or asone among many applications of general purpose hardware. Accordingly, itshould be recognized that the techniques can be realized on a variety ofdifferent instruments or devices utilized for electrical power systemdiagnostics and maintenance.

Discharges on electric power systems exhibit a variety ofcharacteristics. Typically, a discharge will occur when two pieces ofmetal on a powerline are separated by a small gap (e.g., 1 mm) and thereis a voltage gradient between the metal parts (e.g., 1000+ V.). In a 60Hz power system, there will typically be one or more discharges in eachhalf cycle. Each such sparking source can be characterized in severalways. For example, by the number of discharges per half cycle, by theamplitude of the discharges, the location of the discharges on thephase, the spacing of the discharges, and the time density of thedischarges, etc. The discharges radiate electromagnetic and other energy(e.g., acoustic). These characteristics can be observed from the noiseproduced by the discharge using a radio frequency receiver, acousticpick-up, oscilloscope, or the like. Due to differences in gap distance,geometries and size of the metal parts, presence of electricalinsulators, and etc., the discharge characteristics may varysignificantly between individual spark sources on power lines. In manycases, both primary arcs and induced sparks exhibit these variouscharacteristics. It has therefore been a challenge to discovercharacteristics of the discharges upon which to distinguish betweenprimary arc and induced sparks.

According to one implementation of the technique described herein, aninstrument distinguishes discharges from an electric power system sourcethat are primary arcs and those that are induced sparks based on thecharacteristic of the time density of discharges within half of thealternating current cycle of the power system. In observations of powerline sources that can be classified as primary arc and induced sparksources, we have observed that the sources classified to be primary arcswill have a high density of discharges on at least one half cycle, ascompared to the sources classified as induced sparks. If, for example,it is detected that there are more than about 5 pulses in a 100 μsecwindow, it can be surmised that the spark under evaluation is locateddirectly on the primary conductor: i.e., a primary arc. However, if thespark had, for example, only 5 pulses in a period of milliseconds, itwould be identified as an induced spark.

We have further observed that corona type discharges also can producedischarges with a high time density. It can be useful to alsodistinguish primary arcs that are sparking discharges from such coronatype discharges. We have observed that sparking primary arcs will tendto occur on both halves of the electric power system cycle, whereascorona discharges will tend to occur on only one half of the electricpower system cycle. Thus, a further check whether a high density ofpulses occur at intervals corresponding to one half cycle or both halfcycles can be used to further distinguish power line sources that can beclassified as primary arcs from those that are corona.

An exemplary embodiment of an instrument 100 that implements the primaryarc detection technique is shown in FIG. 1. The instrument 100 includesa processing unit 110, such as a microprocessor or microcontroller,which is programmed in firmware to perform a process implementing theprimary arc detection technique (discussed and illustrated in moredetail below). The firmware can be stored in read-only memory (ROM) chip(not shown), on a hard drive or other storage in the instrument.Alternatively, the processing unit 100 can be a digital logic circuit,such as a programmable logic array, which is configured to perform theprocess implementing the primary arc detection technique.

The instrument further includes circuitry for sensing electricaldischarges on a nearby powerline or other electric power systemequipment. The instrument has an antenna 120 and radio frequencyreceiver 130. Alternatively, the instrument can be a sensor for otherenergy radiated from a sparking power line source, such as electricalcurrent, acoustic, oscilloscope, video (base-band) receiver or nearfield probe, among others. The radio frequency receiver 130 provides avideo signal output that is coupled to the non-inverting input of acomparator 140. The comparator 140 generates digital pulses for input tothe microprocessor, which pulses correspond to the power systemdischarges. A network of resistors establishes a threshold for thecomparator 140 based on two inputs: resistors R2, R3 and R4 set aminimum level, while resistors R1 and R2 set a fraction of the peakvideo level. A peak detector circuit formed by capacitor C1 and a diodesenses the voltage peaks on the radio frequency receiver video output.This minimum threshold level and peak video level establish a thresholdat which radio frequency noise on the radio frequency receiver's videosignal output is sensed as an electrical discharge. The digital pulsesfrom the comparator are input to the microprocessor for counting andanalysis.

The instrument also has a display 150 and speaker 160, which arecontrolled by the microprocessor. The instrument presents the result ofthe primary arc identification process on the display 150, such as via atext indication identifying discharges as a primary arc. The displayalso may present other measurements of characteristics of thedischarges, such as the measured pulse time density, peak levels, andetc., if desired. The instrument provides an audio output on the speaker160 corresponding to the radio frequency noise received on the radiofrequency receiver, so that the operator can monitor radio frequencyactivity. The instrument may also provide an audible indication or alertthat a primary arc is detected as a result of the process.

The instrument also includes controls 170, such as buttons, switches,knobs or the like. With the controls 170, the operator of the instrumentcan select between variations or settings for the primary arc detectionprocess, or control sensitivity of the detection process. For example,the illustrated embodiment of the instrument provides multiplevariations of the primary arc detection process. The operator selectsbetween these variations with a switch. This way the operator cancontrol the instrument to selectively use more than one variation of theprimary arc detection process to provide more than one basis fordistinguishing that discharges are primary arcs.

The instrument 100 implements processes 200, 300 shown in FIGS. 2 and 3for distinguishing primary arcs from other electrical discharges in anelectric power system based on pulse time density. The operator of theinstrument can select between variations of the primary arc detectionprocesses with a switch, among the instrument's controls 170.Alternative embodiments of the diagnostic instrument can implement feweror more variations of the primary arc detection process.

A first variation of the primary arc detection process 200 determinesthe maximum number of pulses that occur in any 100 μsec window over aperiod of 250 milliseconds. As shown by action 210, the process countspulses in each 100 μsec window. The 100 μsec windows can benon-overlapping consecutive windows, or alternatively the count can bemade in an overlapping, sliding window manner. Then, the process 200updates a maximum count variable to equal the current window's count, ifthe current window's count exceeds the previous maximum count as shownby actions 211, 212. As shown by the decision 213, the process 200repeats this loop of steps 210-213 for the period of 250 milliseconds.At the end of this period, the maximum count variable will equal themaximum count in any 100 μsec window over the 250 milliseconds period.The duration of the window, the count threshold and period areparameters that can be varied for alternative implementations of theprocess 200.

The process 200 outputs a result on the instrument's display 150 basedon the determined maximum pulse count. Variations of the instrument candisplay the result in a variety of formats, such as a digital value orgraphically (e.g., a bar or the like). The instrument can display theraw maximum pulse count value for the result of the process, which isrelated to a measurement of the pulse time density. Alternatively, theinstrument can scale or otherwise convert the raw pulse count to acalculated pulse time density, such as by dividing the pulse count bythe window duration. Further, in some implementations of the process,the instrument can further compare the maximum pulse count result to arange or threshold characteristic of primary arcs, and output adetermination or indication whether a primary arc has been detectedbased on the comparison. In an exemplary embodiment, the instrumentdetermines that a primary arc is present if the maximum pulse count inany window over the period exceeds 5. However, alternativeimplementations can use a different count threshold or range for theprimary arc detection.

FIG. 3 illustrates a second variation of the primary arc detectionprocess 300. The second variation process 300 again determines a maximumpulse count in any window over a predetermined period, using actions310-313 similar to action 210-213 of the first variation process 200. Inone implementation, the process 300 uses a window of 400 μsec and periodof 16.7 milliseconds. However, different durations of the window andperiod can be chosen in alternative implementations. As illustrated byactions 314-315, the process 300 repeats and records the maximum pulsecounts multiple times. In one implementation, the process 300 performs10 iterations of the maximum pulse count determination, butalternatively a different number of repeated iterations can be used.

At action 316, the process 300 then calculates the mean maximum pulsecount for the multiple iterations. Alternatively, the process maycalculate another statistical combination of the recorded maximum pulsecounts, such as the mode. At action 317, the process 300 outputs aresult for the primary arc detection on the display 150 based on themean maximum pulse count. Similar to the first variation process 200,the second variation process 300 can output the result as the raw meanmaximum pulse count, a pulse time density value calculated based on theraw mean maximum pulse count, or an indication whether a primary arc ispresent based on comparison of the mean maximum pulse count to athreshold or range characteristic of primary arcs (as opposed to inducedcurrent discharges).

Other variations of the primary arc detection process alternatively canbe implemented by the diagnostic instrument. For example, the instrumentcan determine measurements of the pulse time density of electric systemdischarges by sampling pulse counts over various different lengths oftime. The instrument then displays the determination based on pulse timedensity that results from the variation of the process on its display.

With reference to FIG. 4, either of the above operating processes 200,300 can be extended for further distinguishing sparking primary arcsfrom corona type discharges. The extension 400 of the operating processmeasures an interval between the windows having high pulse counts thatexceed a given threshold (e.g., a threshold of 5 pulse counts) as shownin action 410. As indicated by decision block 411 and action 412, if theinterval between high pulse count windows is longer than the periodbetween halves of the electric power system cycle, then the extendedprocess classifies the discharges as corona. Otherwise, if the highpulse count windows occur at intervals of about twice per electric powersystem cycle, then the extended process classifies the discharges asprimary arcs at action 414. With a 60 Hz electric power system, forexample, high pulse count windows occurring on both halves of the cyclecorrespond to an interval of approximately 8.3 msec, whereas theinterval between high pulse counts occurring on only one half the cycleis approximately 16.7 msec. If over-lapping windows are used, a highpulse count can occur in a cluster of neighboring windows within a samehalf of the electric power system cycle. Accordingly, for suchoverlapping window implementations, the extended process identifies afirst high pulse count window out of a cluster of neighboring high pulsecount windows, and measures the interval separating the respectiveinitial window of clusters of overlapping high pulse count windows.Further, because the onset of primary arc discharges may vary betweenhalf cycles, a threshold of somewhat larger than the period between halfcycles (e.g., 9 or 10 msec.) can be used to determine if the intervalbetween high pulse count windows corresponds to fewer than both halvesof the electric power system cycle. Finally, the extended operatingprocess outputs the result identifying whether the discharges arecharacterized as corona or primary arcs.

FIG. 5 illustrates an alternative implementation of an instrument 500implementing the primary arc detection technique. In this alternativeimplementation, the primary arc detection process is implemented inhardware circuitry, rather than in digital logic or programming of amicroprocessor. This alternative implementation instrument 500 alsoincludes an antenna 520 and RF receiver 530 for sensing electromagneticenergy radiated from a sparking power line source. The RF receiver'svideo output is provided to a peak detector and one-shot circuit 540.The circuit 540 produces a pulse with a uniform width (e.g., 2 μsec)when spark noise from an electrical discharge is sensed in the RFreceiver's video output.

The instrument 500 includes an integrator 550 and primary arc detectorcircuit 560. The integrator 550 can be an analog or digital integratorcircuit. In the case of an analog circuit, the integrator produces avoltage signal whose level is related to the time density of noisepulses. The output voltage of the analog integrator increases as thepulses are more closely spaced. For integrating pulses within a windowless than one electric power system cycle, a bleed resistor can beconnected in parallel with the capacitor of the analog integrator. Theresistance of the bleed resistor is chosen such that the analogintegrator has a time constant less the duration of the electric powersystem cycle. For example, a time constant for the analog integrator of2 msec. will ensure the voltage output of the analog integrator returnsto zero in less than one half of the electric power system cycle. As afurther alternative, a low pass filter with a long time constant can beused to perform the function of the integrator 550 in the instrument500. Alternatively, the integrator 550 can be a digital integrator thatproduces a digital value relating to a number of noise pulses occurringwithin a time window or windows equal to or less than a half cycle ofthe electrical power system. The primary arc detector circuit 560 thencompares the integrator circuit output to a threshold or rangecharacteristic of primary arcs. For example, the primary arc detectorcircuit 560 used with an analog integrator 550 can be a voltagecomparator that produces an output signal when the integrator outputvoltage exceeds a threshold voltage. The primary arc detector circuitdrives a display 570, such as an indicator LED or other display.

In view of the many possible embodiments to which the principles of ourinvention may be applied, we claim as our invention all such embodimentsas may come within the scope and spirit of the following claims andequivalents thereto.

We claim:
 1. A method of detecting primary arcs on an electric powersystem, the method comprising: receiving, using an antenna, a radiofrequency sensor signal generated by overhead power transmission ordistribution lines; analyzing the sensor signal to detect noise pulseswithin the sensor signal produced by any nearby electrical discharge,the noise pulses comprising noise pulses caused by primary arcs andnoise pulses caused by induced sparks, wherein primary arcs compriseelectrical discharges occurring on a primary conductor or a secondaryconductor, and wherein induced sparks comprise electrical dischargesoccurring on a structure that is physically common to, but electricallydecoupled from, the primary conductor and the secondary conductor;counting the noise pulses for at least one time duration, wherein eachsaid duration is less than one half cycle of the electric power system,and wherein said counting comprises counting noise pulses in a pluralityof windows over a period of time; determining a measurement related tonoise pulse density based on said counting, the measurementdistinguishing primary arcs from induced sparks in the overhead powertransmission or distribution lines, wherein said determining comprisesdetermining a maximum of the counts of noise pulses in any of thewindows over the period of time; repeating a plurality of iterations ofsaid counting noise pulses in a plurality of windows over a period oftime, wherein said determining comprises determining a statisticalmeasure of the maximum of the counts of noise pulses in any of thewindows over the period of time for the plural iterations; determiningwhether the measurement is in a range characteristic of primary arcs orin a range characteristic of induced sparks; and producing an outputresult based on the measurement, wherein producing an output comprisesdisplaying an indication that a primary arc is detected when themeasurement is determined to be in the range characteristic of primaryarcs.
 2. The method of claim 1, wherein said counting uses consecutivenon-overlapping windows.
 3. The method of claim 1, wherein said countinguses overlapping sliding windows.
 4. The method of claim 1, wherein saidstatistical measure is a mean of the maximum of the counts of noisepulses for the plural iterations.
 5. The method of claim 1 for furtherdistinguishing primary arcs from corona-type discharges, the methodfurther comprising: wherein said counting comprises counting noisepulses in a plurality of time windows over a period of time, the timewindows having durations less than a half cycle of the electric powersystem; measuring an interval between windows with high noise pulsecounts; determining whether said interval corresponds to high noisepulse counts occurring on both or fewer than both halves of an electricpower system cycle; producing an output indicating a primary arc whenthe high noise pulse counts are determined to occur at intervalscorresponding to both halves of the electric power system cycle, andindicating the corona-type discharges when the high noise pulse countsare determined to occur at intervals fewer than both halves of theelectric power system cycle.
 6. A diagnostic instrument fordistinguishing primary arcs from other electrical discharges in anelectric power system, the diagnostic instrument comprising: a receiverto receive, using an antenna, a radio frequency sensor signal generatedby overhead power transmission or distribution lines; a detectioncircuit to detect noise pulses within the sensor signal produced by anynearby electrical discharge, the noise pulses comprising noise pulsescaused by primary arcs and noise pulses caused by induced sparks,wherein primary arcs comprise electrical discharges occurring on aprimary conductor or a secondary conductor, and wherein induced sparkscomprise electrical discharges occurring on a structure that isphysically common to, but electrically decoupled from, the primaryconductor and the secondary conductor; a primary arc identificationcircuit configured for: counting the noise pulses for at least one timeduration, wherein each said duration is less than one half cycle of theelectric power system, and wherein said counting comprises countingnoise pulses in a plurality of windows over a period of time;determining a measurement related to noise pulse density based on saidcounting, the measurement distinguishing primary arcs from inducedsparks in the overhead power transmission or distribution lines, whereinsaid determining comprises determining a maximum of the counts of noisepulses in any of the windows over the period of time; repeating aplurality of iterations of said counting noise pulses in a plurality ofwindows over a period of time, wherein said determining comprisesdetermining a statistical measure of the maximum of the counts of noisepulses in any of the windows over the period of time for the pluraliterations; determining whether the measurement is in a rangecharacteristic of primary arcs or in a range characteristic of inducedsparks; and an output for indicating a result based on the measurement,wherein indicating a result comprises displaying an indication that aprimary arc is detected when the measurement is determined to be in therange characteristic of primary arcs.
 7. The diagnostic instrument ofclaim 6 wherein the primary arc identification circuit comprises: anintegrator circuit coupled to receive the sensed noise pulses from thedetection circuit and producing a voltage output relating to noise pulsetime density; and a primary arc detector circuit coupled to receive thevoltage output of the integrator circuit and produce an outputindicative of whether the noise pulse time density exceeds a thresholdcharacteristic of primary arcs.
 8. The diagnostic instrument of claim 6wherein the primary arc identification circuit comprises a processingunit for determining the measurement related to noise pulse density. 9.The diagnostic instrument of claim 6 wherein the receiver is a radiofrequency, acoustic or video base-band receiver.
 10. The diagnosticinstrument of claim 6 wherein the output is a display of themeasurement.
 11. The diagnostic instrument of claim 6 wherein the outputis a speaker providing an audible indication of the presence of aprimary arc when the measurement is determined to be in the rangecharacteristic of primary arcs.
 12. The diagnostic instrument of claim 6wherein the other electrical discharges include induced sparks orcorona-type discharges, both of which occur on an overhead powertransmission system.
 13. The diagnostic instrument of claim 12 whereinthe plurality of windows are an overlapping sliding window type.
 14. Thediagnostic instrument of claim 12 wherein the plurality of windows are anon-overlapping consecutive window type.
 15. The diagnostic instrumentof claim 6 wherein the statistical measure is a mean.
 16. The diagnosticinstrument of claim 15 wherein the plurality of windows are anoverlapping sliding window type.
 17. The diagnostic instrument of claim15 wherein the plurality of windows are a non-overlapping consecutivewindow type.
 18. The diagnostic instrument of claim 15 wherein theprimary arc identification circuit further operates to determine whetherhigh densities of noise pulses occur in one or both halves of theelectric power system cycle, and to distinguish primary arcs from coronabased on said determination whether high densities of noise pulses occurin both halves of the electric power system cycle.
 19. A diagnosticinstrument for distinguishing primary arcs from other electricaldischarges in an electric power system, the diagnostic instrumentcomprising: a receiver for receiving a signal; a detection circuit forsensing noise pulses on the signal caused by electrical discharges; aprimary arc identification circuit operating to produce a measurementvalue relating to time density of the noise pulses in at least one timeduration wherein each said time duration being less than one half cycleof the electric power system, and to determine whether the measurementvalue is in a range characteristic of primary arcs, as distinguishedfrom other arc types different than primary arcs; and an output forindicating a primary arc detection result when the measurement value isdetermined to be in the range characteristic of primary arcs; whereinthe measurement value is a mean over a plurality of iterations of amaximum count of the noise pulses in any of a plurality of windows overa period of time; and wherein the primary arc identification circuitfurther operates to determine whether high densities of noise pulsesoccur in one or both halves of the electric power system cycle, and todistinguish primary arcs from corona based on said determination whetherhigh densities of noise pulses occur in both halves of the electricpower system cycle.